An integrated optimization approach using a collaborative strategy for sustainable cities freight transportation: A Case study. (December 2021)

• Record Type: Journal Article
• Authors: Aloui, Aymen; Hamani, Nadia; Delahoche, Laurent
• Is Part Of: Sustainable cities and society. Volume 75(2021)
• Publication Date: 2021-12
• Subjects: Collaborative city logistics -- Integrated planning -- Sustainable freight transport -- Mixed-Integer linear programming -- Heuristic -- Collaborative inventory-location-routing problem; Sustainable urban development -- Periodicals; Sustainable buildings -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.76
• DOI: 10.1016/j.scs.2021.103331
• Languages: English
• ISSNs: 2210-6707

Abstract

Highlights: Logistics collaboration is studied in the planning of sustainable city freight transportation. An integrated and collaborative approach is proposed for sustainable freight logistics networks. Three sustainability dimensions are considered. A case study is conducted to show the applicability of proposed approach and the effects of collaboration on the sustainable development of the society and the environment. Abstract: In recent years, the increasing freight transportation activities has caused extensive economic, environmental and social impacts on society. Therefore, it becomes necessary for logistics companies to find high-performance strategies to enhance their sustainability. Collaboration between companies appears as one of the promising solution that improves the freight transport efficiency of modern cities. Existing studies on collaborative transport did not sufficiently account for sustainability aspects and they mainly discuss the independent planning of decision-making problems with economic objectives. However, collaboration an integrated decision-making process can significantly ameliorate the effectiveness of urban transportation systems. This study addresses the issue of sustainable freight transportation planning by formulating and solving a collaborative and integrated two-echelon inventory, location and routing problem (2E-CILRP). The 2E-CILRP is formulated as a multi-objective integer programming model that minimizes logistics costs, C O 2 emissions and accident rate. A hybrid heuristic based on machine learning is also introduced to solve the studied problem. The proposed approach combines k -means clustering and genetic algorithms. Comparison of the obtained results with those provided with exact method reveals that the developed approach is more efficient and more practical for designing integrated and collaborative networks with large-sized data. A case study of four agri-food SMEs in France is investigated in order to demonstrate the sustainable benefits of the developed optimization approach. The obtained results suggest that the developed approach can significantly reduce the level of C O 2 emissions, logistics costs and accident rate caused by transportation in cities.